Author(s): MA, G., QIU, J., LU, J.J., WANG, J.H., Institution: SHANGHAI RESEARCH INSTITUTE OF SPORTS SCIENCE, Country: CHINA, Abstract-ID: 533

INTRODUCTION:
Cycling is a periodic physical event that is associated with high exercise intensity and high-energy expenditure. Accurate measurement of energy expenditure in the course of daily training and competition is crucial in evaluating the amount of training and rational supply of energy for cyclists. Calculation of energy expenditure in exercise using gas metabolic parameters is generally considered accurate [1]. However, the test has a high demand for equipment, facilities and skills. Accelerometry is a well accepted method for measuring physical activity in population-based studies of free-living individuals [2]. It can provide valid and reliable estimates of physical activity [3]. The aim of this study was to investigate the relationship of heart rate (HR), accelerometer counts, and energy expenditure in cyclists during a graded exercise stress test (GXT) on the cycle ergometer.
METHODS:
Twenty male cyclists (mean age 15.7 ± 2.4 years) were selected from the Shanghai Cycling Team. Gas metabolic parameters were determined by cardiopulmonary analysis. Heart rate was telemetered by HR monitoring. After a 10 min warm-up, a GXT on Wattbike was started from 60 rpm with 5 rpm increments every 2 min for a nine-level cycling test. Kinematic parameters included power and cadence. Two energy expenditure indicators were calculated, and acceleration test indicators included triaxial accelerometer counts on the coronal (x), sagittal (y), and vertical axes (z) of the left knee and ankle. Two integrated triaxial accelerometer counts were also calculated. Pearson correlation analysis evaluated the relationship among ACx, ACy, ACz, VM, power and cadence, and EEHR and EES of the knee and ankle in GXT. Relationship was considered statistically significant by r > 0.7.
RESULTS:
We found that cadence and power were correlated with EES (r > 0.9). Since most energy of the cyclist is used for mechanical work during GXT, work directly reflects levels of energy expenditure in the cyclist. Incremental cadence GXT directly reflected the level of energy expenditure in the cyclist. We showed that power in the range of 100–300 W was correlated with EES. The level of correlation between EES and cadence declined as cadence increased, possibly due to small sample size and individual athletic ability.
CONCLUSION:
In the cycle ergometer GXT of an incremental cadence cycling mode, an integrated count from the ankle-worn triaxial accelerometer might be more effective than the knee-worn triaxial accelerometer for predicting cycling activity energy expenditures.